Statistical Methods

Undergraduate course

Course description

Objectives and Content


To give an introduction to statistical methods and suited to students of science. Together with STAT110 it is a natural unit in statistics.


Comparisons of two samples, analysis of variance and experimental design. Bivariate normal distribution, correlation and simple regression. An introduction to nonparametric methods and Bayesian statistics is also given. Examples are given from several areas of application. Some topics from probability theory are also covered, such as transformations of random variables, moment generating function and order statistics. Use of the statistical software package R.

Learning Outcomes


The student

  • Can use basic statistical methods, and understand the mathematical foundation of these
  • Understands the principles for data analysis
  • Bivariate normal distribution and correlation
  • Order statistics
  • Confidence intervals and tests for variances
  • Regression analysis
  • Goodness of fit tests and contingency tables.
  • Analysis of variance: one and two ways
  • Nonparametric methods (Wilcoxon)
  • Bayesian methods
  • The statistical software package R

General competence

The student

  • Has a practical understanding of the probability concept as it used broadly in society
  • Perform and interpret statistical analyses
  • Can program in the software package R, and can interpret output from R

Semester of Instruction

Recommended Previous Knowledge
Credit Reduction due to Course Overlap



Compulsory Assignments and Attendance
Forms of Assessment

Written examination: 4 hours.

Examination support materials: Non- programmable calculator, according to model listed in faculty regulations

Grading Scale
The grading scale used is A to F. Grade A is the highest passing grade in the grading scale, grade F is a fail.